Staff profile

• Statistics
• Applied Statistics
• Uncertainty Analysis
• Statistical Computation
• Variable Selection

Chapter in book

• Hasan, M. M., & Cumming, J. A. (2021). Bayes Linear Emulation of Simulated Crop Yield. In Y. P. Chaubey, S. Lahmiri, F. Nebebe, & A. Sen (Eds.), Applied Statistics and Data Science:Proceedings of Statistics 2021 Canada, Selected Contributions (145-151). Springer Verlag. https://doi.org/10.1007/978-3-030-86133-9_7
• Errington, A., Einbeck, J., & Cumming, J. (2021). Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches. In M. Vasile, & D. Quagliarella (Eds.), Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications (393-405). Springer Verlag. https://doi.org/10.1007/978-3-030-80542-5_24
• Cumming, J., & Goldstein, M. (2010). Bayes linear Uncertainty Analysis for Oil Reservoirs Based on Multiscale Computer Experiments. In A. O'Hagan, & M. West (Eds.), The Oxford handbook of applied Bayesian analysis (241-270). Oxford University Press

Conference Paper

• Jaffrezic, V., Razminia, K., Cumming, J., & Gringarten, A. (2019, December). Field Applications of Constrained Multiwell Deconvolution. Presented at SPE Europec featured at 81st EAGE Conference and Exhibition, London, UK
• Aluko, L., Cumming, J., & Gringarten, A. (2020, December). Using Deconvolution to Estimate Unknown Well Production from Scarce Wellhead Pressure Data. Presented at SPE Annual Technical Conference and Exhibition, Virtual
• Hasan, M. M., & Cumming, J. (2020, December). A Bayesian non-linear hierarchical framework for crop models based on big data outputs. Paper presented at 13th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2020), King's College London, England
• Cumming, J., Botsas, T., Jermyn, I., & Gringarten, A. (2020, December). Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach. Presented at SPE Virtual Europec 2020
• Cumming, J., Jaffrezic, V., Whittle, T., & Gringarten, A. (2019, August). Constrained Least-Squares Multiwell Deconvolution. Presented at SPE Western Regional Meeting, San Jose, California, USA
• Tung, Y., Virues, C., Cumming, J., & Gringarten, A. (2016, May). Multiwell Deconvolution for Shale Gas. Presented at SPE Europec featured at 78th EAGE Conference and Exhibition, Vienna, Austria
• Thornton, E., Mazloom, J., Gringarten, A., & Cumming, J. (2015, December). Application of Multiple Well Deconvolution Method in a North Sea Field. Presented at EUROPEC 2015, Madrid, Spain
• Cumming, J., Wooff, D., Whittle, T., & Gringarten, A. (2013, December). Multiple Well Deconvolution. Presented at 2013 SPE Annual Technical Conference & Exhibition, New Orleans, USA
• Cumming, J., Wooff, D., Whittle, T., Crossman, R., & Gringarten, A. (2013, December). Assessing the Non-Uniqueness of the Well Test Interpretation Model Using Deconvolution. Presented at 75th EAGE Annual Conference & Exhibition, 10–13 June 2013, London, United Kingdom

Doctoral Thesis

• Cumming, J. (2006). Clinical Decision Support. (Thesis). Department of Mathematical Sciences, Durham University. https://durham-repository.worktribe.com/output/1642189

Journal Article

• Botsas, T., Cumming, J., & Jermyn, I. (2022). A Bayesian multi-region radial composite reservoir model for deconvolution in well test analysis. Journal of the Royal Statistical Society: Series C, 71(4), 951-968. https://doi.org/10.1111/rssc.12562
• Errington, A., Einbeck, J., Cumming, J., Rössler, U., & Endesfelder, D. (2022). The effect of data aggregation on dispersion estimates in count data models. International Journal of Biostatistics, 18(1), 183-202. https://doi.org/10.1515/ijb-2020-0079
• Goldie, S. J., Bush, S., Cumming, J. A., & Coleman, K. S. (2020). Statistical Approach to Raman Analysis of Graphene-Related Materials: Implications for Quality Control. ACS Applied Nano Material, 3(11), 11229-11239. https://doi.org/10.1021/acsanm.0c02361
• Vernon, I., Jackson, S., & Cumming, J. (2019). Known Boundary Emulation of Complex Computer Models. SIAM/ASA Journal on Uncertainty Quantification, 7(3), 838-876. https://doi.org/10.1137/18m1164457
• Cumming, J., Wooff, D., Whittle, T., & Gringarten, A. (2014). Multiwell Deconvolution. SPE Reservoir Evaluation & Engineering, 17(04), 457-465. https://doi.org/10.2118/166458-pa
• Cumming, J., & Goldstein, M. (2009). Small Sample Bayesian Designs for Complex High-Dimensional Models Based on Information Gained Using Fast Approximations. Technometrics, 51(4), 377-388. https://doi.org/10.1198/tech.2009.08015
• Cumming, J., & Wooff, D. (2007). Dimension reduction via principal variables. Computational Statistics & Data Analysis, 52(1), 550-565. https://doi.org/10.1016/j.csda.2007.02.012

Report

• Cumming, J., Riseth, A., & Williams, J. (2016). Understanding the accuracy of pre-symptomatic diagnosis of sepsis. [No known commissioning body]